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In transformer models, text is first split into tokens, small units like words or parts of words. Each token is then converted into a vector, which is essentially a set of numbers that captures its me
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AlexNet learns features in layers, becoming more abstract as information moves deeper through the network. The early convolutional layers focus on simple patterns like edges, lines, and color contrast
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Convolutions work by using a small filter, also called a kernel, that moves across a grid of values like an image. At each position, the filter multiplies its values with the underlying grid and adds
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In transformers, each word or token is represented as a vector in a space with many dimensions. But there’s a limit to how many completely independent vectors can exist in that space. For vectors to b
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A transformer is made up of three core components that work together: attention, MLP (feed forward) layers, and normalization. The attention layer lets each token figure out which other tokens matter
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Most people see neural networks as something mysterious, but in reality it’s just math trying to find the best possible boundary. The hard part isn’t reading about layers and nodes, it’s actually visu
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Linear regression is one of the most basic and widely used algorithms in machine learning. It helps you understand and predict how one number changes in relation to another. At its core, it draws a s
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Most people think AI reads text the way humans do, but that’s not what’s happening. Instead, every word gets placed as a coordinate in a huge multidimensional space. The real innovation isn’t just map
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Cosine similarity is a way of measuring how alike two vectors are by looking at the angle between them rather than their size. This makes it especially useful for high-dimensional data like embeddings
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You think AI reads words. It doesn’t. It does math. Everyone is talking about LLMs right now, but very few understand what’s actually happening when you type a prompt. If you want to build powerful A
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Principal Component Analysis (PCA) is an unsupervised learning method used to simplify complex datasets by reducing the number of variables while keeping as much important information as possible. It
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Perplexity has just become the first AI company to seriously challenge the Bloomberg Terminal head-on. Credits: The artificial intelligence Follow @datascience.swat for more daily videos like this
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About @datascience.swat

Data Science | Machine Learning | Algorithms is a Instagram nano influencer. With 6.6K followers and 68 posts, datascience.swat's account shows a follower-to-following ratio of 548.3:1. View all content anonymously on Pictame - no login required.

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4.82% engagement rate — right on track for 1K-10K follower accounts.
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Data Science | Machine Learning | Algorithms

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